Evidence map›Paper›PMID 35439968›Full record

ArticleBMC psychiatry2022

Characteristics of depression, anxiety, impulsivity, and aggression among various types of drug users and factors for developing severe depression: a cross-sectional study.

Dan Luo, Lu Tan, Danlin Shen, Zhe Gao, LiangMing Yu, Mingfeng Lai, Jiajun Xu, Jing Li

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Dan LuoMental Health Center, West China Hospital of Sichuan University, 28 Dian Xin Nan Jie, Chengdu, 610041, Sichuan, China.
Lu TanSleep Medicine Center, West China Hospital of Sichuan University, Chengdu, China.
Danlin ShenMental Health Center, West China Hospital of Sichuan University, 28 Dian Xin Nan Jie, Chengdu, 610041, Sichuan, China.
Zhe GaoMental Health Center, West China Hospital of Sichuan University, 28 Dian Xin Nan Jie, Chengdu, 610041, Sichuan, China.
LiangMing YuMental Health Center, West China Hospital of Sichuan University, 28 Dian Xin Nan Jie, Chengdu, 610041, Sichuan, China.
Mingfeng LaiMental Health Center, West China Hospital of Sichuan University, 28 Dian Xin Nan Jie, Chengdu, 610041, Sichuan, China.
Jiajun XuMental Health Center, West China Hospital of Sichuan University, 28 Dian Xin Nan Jie, Chengdu, 610041, Sichuan, China. xujiajun120@126.com.
Jing LiMental Health Center, West China Hospital of Sichuan University, 28 Dian Xin Nan Jie, Chengdu, 610041, Sichuan, China. joana028@163.com.
Sichuan University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMood disorder, impulsivity and aggression are common in drug users compared to healthy controls. However, no study has focused on the difference in various types of drug users. Therefore, the objective of this study was to explore the differences in depression, anxiety, impulsivity, and aggression among methamphetamine, heroin and polysubstance users and to further explore the risk factors for severe depression in the three groups.

methodsDrug users over 18 years old who met the DSM-V diagnostic criteria for substance -related disorders were included in the study. All participants completed a general questionnaire, the Zung Self-Rating Depression Scale (SDS), the Zung Self-Rating Anxiety Scale (SAS), Barratt impulsiveness Scale Version 11 (BIS-11), and the Buss-Perry Aggression Questionnaire (BPAQ). One-way ANOVAs or Chi-square tests were used to test the differences among the groups, correlation analysis was used to test the relationship between drug use and other parameters, and multiple logistic regression was conducted to assess the risk factors for severe depression.

resultsA total of 1,486 participants were included, comprising 86.3% males with a mean age of 38.97 years. There was a significant difference in the percentage of severe depression and SDS scores among the three groups, but no significant difference was found in SAS, BIS-11 and BPAQ scores. Using methamphetamines, hostility and anxiety were risk factors for developing severe depression in all the participants and anxiety remained constant in the other three groups. Moreover, methamphetamine use was 2.16 and 3.35 times more likely to cause severe depression than heroin and polysubstance use, respectively. The initial age of substance use was negatively correlated with BPAQ, SAS, and SDS scores, whereas the drug use duration and addiction duration were positively correlated.

conclusionsIn this study, we found that the highest prevalence of severe depression was in participants using methamphetamines and that using methamphetamines, hostility, and anxiety were risk factors for developing severe depression. This result addressed an important gap in our knowledge of the different characteristics of depression, anxiety, impulsivity and aggression in various types of substance users and provides clinicians and policy-makers with directions for intervention and preventing relapse.

Indexed as

Drug UsersMajor Depressive DisorderMethamphetamineSubstance-Related DisordersAdolescentAdultAggressionAnxietyCross-Sectional StudiesDepressionFemaleHeroinHumansImpulsive BehaviorMaleHeroinMethamphetamineAggressionHeroinImpulsivityMethamphetamineSevere depression

Identifiers

PMID35439968
PMCPMC9020049
OpenAlexW4224308777

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.